An exploration on the machine-learning-based stroke prediction model.

Introduction: With the rapid development of artificial intelligence technology, machine learning algorithms have been widely applied at various stages of stroke diagnosis, treatment, and prognosis, demonstrating significant potential. A correlation between stroke and cytokine levels in the human body has recently been reported. Our study aimed to establish machine-learning models based on cytokine features to enhance the decision-making capabilities of clinical physicians. Methods: This study recruited 2346 stroke patients and 2128 healthy control subjects from Chongqing University Central Hospital. A predictive model was established through clinical experiments and collection of clinical laboratory tests and demographic variables at admission. Three classification algorithms, namely Random Forest, Gradient Boosting, and Support Vector Machine, were employed. The models were evaluated using methods such as ROC curves, AUC values, and calibration curves. Results: Through univariate feature selection, we selected 14 features and constructed three machine-learning models: Support Vector Machine (SVM), Random Forest (RF), and Gradient Boosting Machine (GBM). Our results indicated that in the training set, the RF model outperformed the GBM and SVM models in terms of both the AUC value and sensitivity. We ranked the features using the RF algorithm, and the results showed that IL-6, IL-5, IL-10, and IL-2 had high importance scores and ranked at the top. In the test set, the stroke model demonstrated a good generalization ability, as evidenced by the ROC curve, confusion matrix, and calibration curve, confirming its reliability as a predictive model for stroke. Discussion: We focused on utilizing cytokines as features to establish stroke prediction models. Analyses of the ROC curve, confusion matrix, and calibration curve of the test set demonstrated that our models exhibited a strong generalization ability, which could be applied in stroke prediction.

Physiomimetic Fluidic Culture Platform on Microwell-Patterned Porous Collagen Scaffold for Human Pancreatic Islets.

Pancreatic islet transplantation is one of the clinical options for certain types of diabetes. However, difficulty in maintaining islets prior to transplantation limits the clinical expansion of islet transplantations. Our study introduces a dynamic culture platform developed specifically for primary human islets by mimicking the physiological microenvironment, including tissue fluidics and extracellular matrix support. We engineered the dynamic culture system by incorporating our distinctive microwell-patterned porous collagen scaffolds for loading isolated human islets, enabling vertical medium flow through the scaffolds. The dynamic culture system featured four 12 mm diameter islet culture chambers, each capable of accommodating 500 islet equivalents (IEQ) per chamber. This configuration calculates > five-fold higher seeding density than the conventional islet culture in flasks prior to the clinical transplantations (442 vs 86 IEQ/cm2). We tested our culture platform with three separate batches of human islets isolated from deceased donors for an extended period of 2 weeks, exceeding the limits of conventional culture methods for preserving islet quality. Static cultures served as controls. The computational simulation revealed that the dynamic culture reduced the islet volume exposed to the lethal hypoxia (< 10 mmHg) to ~1/3 of the static culture. Dynamic culture ameliorated the morphological islet degradation in long-term culture and maintained islet viability, with reduced expressions of hypoxia markers. Furthermore, dynamic culture maintained the islet metabolism and insulin-secreting function over static culture in a long-term culture. Collectively, the physiological microenvironment-mimetic culture platform supported the viability and quality of isolated human islets at high-seeding density. Such a platform has a high potential for broad applications in cell therapies and tissue engineering, including extended islet culture prior to clinical islet transplantations and extended culture of stem cell-derived islets for maturation.

Glioblastoma stem cells deliver ABCB4 transcribed by ATF3 via exosomes conferring glioblastoma resistance to temozolomide.

Glioblastoma stem cells (GSCs) play a key role in glioblastoma (GBM) resistance to temozolomide (TMZ) chemotherapy. With the increase in research on the tumour microenvironment, exosomes secreted by GSCs have become a new focus in GBM research. However, the molecular mechanism by which GSCs affect drug resistance in GBM cells via exosomes remains unclear. Using bioinformatics analysis, we identified the specific expression of ABCB4 in GSCs. Subsequently, we established GSC cell lines and used ultracentrifugation to extract secreted exosomes. We conducted in vitro and in vivo investigations to validate the promoting effect of ABCB4 and ABCB4-containing exosomes on TMZ resistance. Finally, to identify the transcription factors regulating the transcription of ABCB4, we performed luciferase assays and chromatin immunoprecipitation-quantitative PCR. Our results indicated that ABCB4 is highly expressed in GSCs. Moreover, high expression of ABCB4 promoted the resistance of GSCs to TMZ. Our study found that GSCs can also transmit their highly expressed ABCB4 to differentiated glioma cells (DGCs) through exosomes, leading to high expression of ABCB4 in these cells and promoting their resistance to TMZ. Mechanistic studies have shown that the overexpression of ABCB4 in GSCs is mediated by the transcription factor ATF3. In conclusion, our results indicate that GSCs can confer resistance to TMZ in GBM by transmitting ABCB4, which is transcribed by ATF3, through exosomes. This mechanism may lead to drug resistance and recurrence of GBM. These findings contribute to a deeper understanding of the mechanisms underlying drug resistance in GBM and provide novel insights into its treatment.

Effect of Hydrogel Stiffness on Chemoresistance of Breast Cancer Cells in 3D Culture.

Chemotherapy is one of the most common strategies for cancer treatment, whereas drug resistance reduces the efficiency of chemotherapy and leads to treatment failure. The mechanism of emerging chemoresistance is complex and the effect of extracellular matrix (ECM) surrounding cells may contribute to drug resistance. Although it is well known that ECM plays an important role in orchestrating cell functions, it remains exclusive how ECM stiffness affects drug resistance. In this study, we prepared agarose hydrogels of different stiffnesses to investigate the effect of hydrogel stiffness on the chemoresistance of breast cancer cells to doxorubicin (DOX). Agarose hydrogels with a stiffness range of 1.5 kPa to 112.3 kPa were prepared and used to encapsulate breast cancer cells for a three-dimensional culture with different concentrations of DOX. The viability of the cells cultured in the hydrogels was dependent on both DOX concentration and hydrogel stiffness. Cell viability decreased with DOX concentration when the cells were cultured in the same stiffness hydrogels. When DOX concentration was the same, breast cancer cells showed higher viability in high-stiffness hydrogels than they did in low-stiffness hydrogels. Furthermore, the expression of P-glycoprotein mRNA in high-stiffness hydrogels was higher than that in low-stiffness hydrogels. The results suggested that hydrogel stiffness could affect the resistance of breast cancer cells to DOX by regulating the expression of chemoresistance-related genes.

Smart composite scaffold to synchronize magnetic hyperthermia and chemotherapy for efficient breast cancer therapy.

Combination of different therapies is an attractive approach for cancer therapy. However, it is a challenge to synchronize different therapies for maximization of therapeutic effects. In this work, a smart composite scaffold that could synchronize magnetic hyperthermia and chemotherapy was prepared by hybridization of magnetic Fe3O4 nanoparticles and doxorubicin (Dox)-loaded thermosensitive liposomes with biodegradable polymers. Irradiation of alternating magnetic field (AMF) could not only increase the scaffold temperature for magnetic hyperthermia but also trigger the release of Dox for chemotherapy. The two functions of magnetic hyperthermia and chemotherapy were synchronized by switching AMF on and off. The synergistic anticancer effects of the composite scaffold were confirmed by in vitro cell culture and in vivo animal experiments. The composite scaffold could efficiently eliminate breast cancer cells under AMF irradiation. Moreover, the scaffold could support proliferation and adipogenic differentiation of mesenchymal stem cells for adipose tissue reconstruction after anticancer treatment. In vivo regeneration experiments showed that the composite scaffolds could effectively maintain their structural integrity and facilitate the infiltration and proliferation of normal cells within the scaffolds. The composite scaffold possesses multi-functions and is attractive as a novel platform for efficient breast cancer therapy.

Nanoparticles Coated with Brain Microvascular Endothelial Cell Membranes can Target and Cross the Blood-Brain Barrier to Deliver Drugs to Brain Tumors.

The blood-brain barrier (BBB) contains tightly connected brain microvascular endothelial cells (BMECs) that hinder drug delivery to the brain, which makes brain tumors difficult to treat. Previous studies have shown that nanoparticles coated with tumor cell membranes selectively target their homologous tumors. Therefore, this study investigated whether bEnd.3-line BMEC membrane-coated nanoparticles with poly(lactide-co-glycolide)-poly(ethylene glycol)-based doxorubicin-loaded cores (BM-PDs) can be used to target BMECs and cross the BBB. In vitro, the BM-PDs effectively target BMECs and cross a BBB model. The BM-PDs enter the BMECs via macropinocytosis, clathrin-mediated endocytosis, caveolin-mediated endocytosis, and membrane fusion, which result in excellent cellular uptake. The BM-PDs also show excellent cellular uptake in brain tumor cells. In vivo, the BM-PDs target BMECs, cross the BBB, accumulate in brain tumors, and efficiently kill tumor cells. Therefore, the proposed strategy has great therapeutic potential owing to its ability to cross the BBB to reach brain tumors.

ZNF148 inhibits HBV replication by downregulating RXRα transcription.

BACKGROUND: Progressive hepatitis B virus (HBV) infection can result in cirrhosis, hepatocellular cancer, and chronic hepatitis. While antiviral drugs that are now on the market are efficient in controlling HBV infection, finding a functional cure is still quite difficult. Identifying host factors involved in regulating the HBV life cycle will contribute to the development of new antiviral strategies. Zinc finger proteins have a significant function in HBV replication, according to earlier studies. Zinc finger protein 148 (ZNF148), a zinc finger transcription factor, regulates the expression of various genes by specifically binding to GC-rich sequences within promoter regions. The function of ZNF148 in HBV replication was investigated in this study. METHODS: HepG2-Na+/taurocholate cotransporting polypeptide (HepG2-NTCP) cells and Huh7 cells were used to evaluate the function of ZNF148 in vitro. Northern blotting and real-time PCR were used to quantify the amount of viral RNA. Southern blotting and real-time PCR were used to quantify the amount of viral DNA. Viral protein levels were elevated, according to the Western blot results. Dual-luciferase reporter assays were used to examine the transcriptional activity of viral promoters. ZNF148's impact on HBV in vivo was investigated using an established rcccDNA mouse model. RESULTS: ZNF148 overexpression significantly decreased the levels of HBV RNAs and HBV core DNA in HBV-infected HepG2-NTCP cells and Huh7 cells expressing prcccDNA. Silencing ZNF148 exhibited the opposite effects in both cell lines. Furthermore, ZNF148 inhibited the activity of HBV ENII/Cp and the transcriptional activity of cccDNA. Mechanistic studies revealed that ZNF148 attenuated retinoid X receptor alpha (RXRα) expression by binding to the RXRα promoter sequence. RXRα binding site mutation or RXRα overexpression abolished the suppressive effect of ZNF148 on HBV replication. The inhibitory effect of ZNF148 was also observed in the rcccDNA mouse model. CONCLUSIONS: ZNF148 inhibited HBV replication by downregulating RXRα transcription. Our findings reveal that ZNF148 may be a new target for anti-HBV strategies.

Establishment and analysis of a novel diagnostic model for systemic juvenile idiopathic arthritis based on machine learning.

BACKGROUND: Systemic juvenile idiopathic arthritis (SJIA) is a form of childhood arthritis with clinical features such as fever, lymphadenopathy, arthritis, rash, and serositis. It seriously affects the growth and development of children and has a high rate of disability and mortality. SJIA may result from genetic, infectious, or autoimmune factors since the precise source of the disease is unknown. Our study aims to develop a genetic-based diagnostic model to explore the identification of SJIA at the genetic level. METHODS: The gene expression dataset of peripheral blood mononuclear cell (PBMC) samples from SJIA was collected from the Gene Expression Omnibus (GEO) database. Then, three GEO datasets (GSE11907-GPL96, GSE8650-GPL96 and GSE13501) were merged and used as a training dataset, which included 125 SJIA samples and 92 health samples. GSE7753 was used as a validation dataset. The limma method was used to screen differentially expressed genes (DEGs). Feature selection was performed using Lasso, random forest (RF)-recursive feature elimination (RFE) and RF classifier. RESULTS: We finally identified 4 key genes (ALDH1A1, CEACAM1, YBX3 and SLC6A8) that were essential to distinguish SJIA from healthy samples. And we combined the 4 key genes and performed a grid search as well as 10-fold cross-validation with 5 repetitions to finally identify the RF model with optimal mtry. The mean area under the curve (AUC) value for 5-fold cross-validation was greater than 0.95. The model's performance was then assessed once more using the validation dataset, and an AUC value of 0.990 was obtained. All of the above AUC values demonstrated the strong robustness of the SJIA diagnostic model. CONCLUSIONS: We successfully developed a new SJIA diagnostic model that can be used for a novel aid in the identification of SJIA. In addition, the identification of 4 key genes that may serve as potential biomarkers for SJIA provides new insights to further understand the mechanisms of SJIA.

Correlation between blood glucose level and poor wound healing after posterior lumbar interbody fusion in patients with type 2 diabetes.

To investigate the correlation of blood glucose level with poor wound healing (PWH) after posterior lumbar interbody fusion (PLIF) in patients with type 2 diabetes (T2D). From January 2016 to January 2023, a case-control study was conducted to analyse the clinical data of 400 patients with T2D who were treated by PLIF and internal fixation at our hospital. The following data were recorded: gender; age; body mass index (BMI); surgical stage; average perioperative blood glucose level; perioperative blood glucose variance; perioperative blood glucose coefficient of variation; glycated haemoglobin level; preoperative levels of total protein, albumin and haemoglobin; postoperative levels of total protein, albumin and haemoglobin; surgical time; intraoperative bleeding volume; operator; postoperative drainage volume; and postoperative drainage tube removal time of each group. The indicators for monitoring blood glucose variability (GV) included the SD of blood glucose level (SDBG), coefficient of variation (CV) and maximum amplitude of variation (LAGE) before and after surgery. According to the diagnostic criteria for PWH, patients with postoperative PWH were determined and assigned to two groups: Group A (good wound healing group; n = 330 patients) and Group B (poor wound healing group; n = 70 patients). The preoperative and postoperative blood GV indicators, namely SDBG, CV and LAGE, were compared between these two groups. We also determined the relationship between perioperative blood GV parameters and PWH after PLIF surgery and its predictive value through correlation analysis and receiver-operating characteristic curve. Of the 400 enrolled patients, 70 patients had PWH. Univariate analysis revealed significant differences between the two groups in the course of diabetes, mean fasting blood glucose (MFBG), SDBG, CV, LAGE, preoperative hypoglycaemic program, surgical segment, postoperative drainage time, incision length and other factors (p < 0.05). However, no significant differences were noted in factors such as gender, age, body mass index, hypertension, coronary heart disease, admission fasting blood glucose, preoperative haemoglobin A1c, surgical time, intraoperative bleeding volume, intraoperative blood transfusion volume and postoperative drainage volume (p > 0.05). The area under the curve (AUC) values of preoperative SDBG, CV and LAGE were 0.6657, 0.6432 and 0.6584, respectively. The cut-off values were 1.13 mmol/L, 6.97% and 0.75 mmol/L, respectively. The AUC values for postoperative SDBG, CV and LAGE were 0.5885, 0.6255 and 0.6261, respectively. The cut-off values were 1.94 mmol/L, 24.32% and 2.75 mmol/L, respectively. The multivariate ridge regression analysis showed that preoperative MFBG, SDBG, CV and LAGE; postoperative SDBG, CV and LAGE; postoperative long drainage time; and multiple surgical segments were independent risk factors for T2D patients to develop surgical site infection after PLIF (p < 0.05). The perioperative blood GV in patients with T2D is closely related to the occurrence of PWH after PLIF. Reducing blood GV may help to reduce the occurrence of PWH after PLIF.

Efficacy of surgical treatment and conservative treatment for cervical spinal cord injury without fracture and dislocation in adults: A meta-analysis.

BACKGROUND: The aim of this study was to investigate the efficacy of surgical treatment and conservative treatment for cervical spinal cord injury without fracture and dislocation (CSCIWFD) in adults by meta-analysis. METHODS: With a time span from 2010 to 2022, PubMed, Web of Science, Embase, China National Knowledge Infrastructure (CNKI) and Wanfang databases were searched for all clinical randomized controlled trials on the comparison of surgical treatment and conservative treatment for CSCIWFD in adults. The Cochrane quality assessment tool was used as the standard. Stata 16.0 statistical software was used for meta-analysis. RESULTS: A total of 870 articles were retrieved, and 12 studies were finally included for meta-analysis. Among them, there were 451 patients in the observation group (surgical treatment) and 346 patients in the control group (conservative treatment). The results of meta-analysis showed that the observation group was superior to the control group in the effective rate (OR = 4.737, 95% CI [2.613, 8.586], P < .001), Japanese Orthopedic Association (JOA) score at 3 months after treatment (SMD = 1.038, 95% CI [0.417, 1.659], P = .001), 6 months after treatment (SMD = 3.135, 95% CI [2.120, 4.151], P < .001) and 12 months after treatment (SMD = 2.808, 95% CI [1.880, 3.737], P < .001). In addition, the JOA scores of patients at 12 months after surgical treatment (SMD = 6.397, 95% CI [4.654, 8.14], P < .001) and conservative treatment (SMD = 3.197, 95% CI [2.144, 4.24], P < .001) were significantly higher than those before treatment. CONCLUSIONS: Surgical treatment can improve the effective rate and JOA score of adult patients with CSCIWFD compared to conservative treatment. This suggests that surgical treatment can significantly improve the patient's spinal cord function.

Inflammatory responsive neutrophil-like membrane-based drug delivery system for post-surgical glioblastoma therapy.

Surgical resection of glioblastoma (GBM) causes brain inflammation that activates and recruits neutrophils (NEs) to residual GBM tissues. NE-based drug delivery using inflammatory chemotaxis is promising for the post-surgical treatment of residual GBM, but its clinical application is limited by the short life span of NEs and lack of in vitro propagation methods. HL60 cells are a type of infinitely multiplying tumor cells that can be induced to differentiate into NE-like cells. We developed a novel NE-like membrane system (NM-PD) by coating NE-like membranes on the surface of poly (lactide-co-glycolide)-poly(ethylene glycol) (PLGA-PEG)-based doxorubicin (DOX)-loaded core (PLGA-PEG-DOX, PD) for post-surgical residual GBM treatment. Cell adhesion proteins were detected on NE-like membranes and endowed NM-PDs with inflammatory chemotaxis similar to mature NEs. The resulting NM-PD shows excellent inflamed in vitro blood-brain barrier (BBB) permeability and anti-proliferative effects on GBM cells. In our intracranial GBM resection model, NM-PD exhibited superior inflammatory chemotaxis and targeted residual GBM cells, thus remarkably improving antitumor capability and prolonging the survival time of the mice. These data suggest that NM-PD, which has sufficient sources and is easy to prepare, can efficiently suppress post-surgical residual GBM and holds potential for clinical transformation in GBM post-surgical adjuvant therapy.

3D culture of bovine articular chondrocytes in viscous medium encapsulated in agarose hydrogels for investigation of viscosity influence on cell functions.

The mechanical properties of an extracellular microenvironment can affect cell functions. The effects of elasticity and viscoelasticity on cell functions have been extensively studied with hydrogels of tunable mechanical properties. However, investigation of the viscosity effect on cell functions is still very limited and it can be tricky to explore how viscosity affects cells in three-dimensional (3D) culture due to the lack of appropriate tools. In this study, agarose hydrogel containers were prepared and used to encapsulate viscous media for 3D cell culture to investigate the viscosity effect on the functions of bovine articular chondrocytes (BACs). Polyethylene glycol of different molecular weights was used to adjust culture medium viscosity in a large range (72.8-679.2 mPa s). The viscosity affected gene expression and secretion of cartilagenious matrices, while it did not affect BAC proliferation. The BACs cultured in the lower viscosity medium (72.8 mPa s) showed a higher level of cartilaginous gene expression and matrix secretion.

Demand prediction of medical services in home and community-based services for older adults in China using machine learning.

Background: Home and community-based services are considered an appropriate and crucial caring method for older adults in China. However, the research examining demand for medical services in HCBS through machine learning techniques and national representative data has not yet been carried out. This study aimed to address the absence of a complete and unified demand assessment system for home and community-based services. Methods: This was a cross-sectional study conducted on 15,312 older adults based on the Chinese Longitudinal Healthy Longevity Survey 2018. Models predicting demand were constructed using five machine-learning methods: Logistic regression, Logistic regression with LASSO regularization, Support Vector Machine, Random Forest, and Extreme Gradient Boosting (XGboost), and based on Andersen's behavioral model of health services use. Methods utilized 60% of older adults to develop the model, 20% of the samples to examine the performance of models, and the remaining 20% of cases to evaluate the robustness of the models. To investigate demand for medical services in HCBS, individual characteristics such as predisposing, enabling, need, and behavior factors constituted four combinations to determine the best model. Results: Random Forest and XGboost models produced the best results, in which both models were over 80% at specificity and produced robust results in the validation set. Andersen's behavioral model allowed for combining odds ratio and estimating the contribution of each variable of Random Forest and XGboost models. The three most critical features that affected older adults required medical services in HCBS were self-rated health, exercise, and education. Conclusion: Andersen's behavioral model combined with machine learning techniques successfully constructed a model with reasonable predictors to predict older adults who may have a higher demand for medical services in HCBS. Furthermore, the model captured their critical characteristics. This method predicting demands could be valuable for the community and managers in arranging limited primary medical resources to promote healthy aging.

Cathepsin H Knockdown Reverses Radioresistance of Hepatocellular Carcinoma via Metabolic Switch Followed by Apoptosis.

Despite the wide application of radiotherapy in HCC, radiotherapy efficacy is sometimes limited due to radioresistance. Although radioresistance is reported with high glycolysis, the underlying mechanism between radioresistance and cancer metabolism, as well as the role of cathepsin H (CTSH) within it, remain unclear. In this study, tumor-bearing models and HCC cell lines were used to observe the effect of CTSH on radioresistance. Proteome mass spectrometry, followed by enrichment analysis, were used to investigate the cascades and targets regulated by CTSH. Technologies such as immunofluorescence co-localization flow cytometry and Western blot were used for further detection and verification. Through these methods, we originally found CTSH knockdown (KD) perturbed aerobic glycolysis and enhanced aerobic respiration, and thus promoted apoptosis through up-regulation and the release of proapoptotic factors such as AIFM1, HTRA2, and DIABLO, consequently reducing radioresistance. We also found that CTSH, together with its regulatory targets (such as PFKL, HK2, LDH, and AIFM1), was correlated with tumorigenesis and poor prognosis. In summary, our study found that the cancer metabolic switch and apoptosis were regulated by CTSH signaling, leading to the occurrence of radioresistance in HCC cells and suggesting the potential value of HCC diagnosis and therapy.

Preoperative administration of a biomimetic platelet nanodrug enhances postoperative drug delivery by bypassing thrombus.

The postoperative thrombus attached to the damaged blood vessels severely obstructs drugs from crossing the damaged blood-brain barrier (BBB) and targeting residual glioma cells around surgical margins, leading to glioblastoma (GBM) recurrence. A thrombus-bypassing, BBB-crossing, and surgical margin-targeted nanodrug is needed to address this phenomenon. Encouraged by the intrinsic damaged vascular endothelium chemotaxis of platelets, a platelet membrane-coated nanodrug (PM-HDOX) delivering doxorubicin (DOX) for postoperative GBM treatment is proposed and systematically investigated. Because surgery damages the vascular endothelium on the BBB around the surgical margin, the platelet membrane coating endows PM-HDOX with its inherent capacity to cross the broken BBB and target the surgical margin. Moreover, preoperative administration combined with fast-targeted PM-HDOX can realize the potential of bypassing thrombus. In GBM resection models, PM-HDOX with preoperative administration demonstrated significantly enhanced BBB-crossing and surgical margin-targeted efficacy. In particular, the PM-HDOX intensities around the surgical margins of the preoperative administration group were more than twice that of the postoperative administration group due to bypassing the thrombus formed in the broken BBB. In the antitumor experiment, the preoperative administration of PM-HDOX significantly inhibited the growth of postoperative residual tumors and prolonged the median survival time of mice. In conclusion, preoperative administration of a biomimetic platelet nanodrug can be an efficient and promising drug delivery strategy for residual GBM after surgery.

Application of the Hoffmann, Bhattacharya, nonparametric test, and Q-Q plot methods for establishing reference intervals from laboratory databases.

BACKGROUND: Reference intervals (RIs) are vital for interpreting laboratory biomarkers and enabling clinical decision-making. Among various RI-estimation methods, we explored the application value of Hoffmann, Bhattacharya, nonparametric test, and Q-Q plot methods for estimating the RI of urea, creatinine, and uric acid (UA). METHOD: This cross-sectional study collected patient data recorded between January 2020 and April 2022 at the Chongqing University Central Hospital Laboratory Information System. The RIs of urea, creatinine, and UA levels were established using the Hoffmann, Bhattacharya, nonparametric, and Q-Q plot methods, and RI differences with different computational methods were verified using the reference change value (RCV%) of biological variability. RESULTS: We included 16,474 and 123,570 patients in the physical examination and clinical groups, respectively. In the clinical group, differences in the RI upper limit of analytes with the four methods (excluding the Q-Q plot method) were within the permissible RCV% range; only the nonparametric test produced an RI of urea with the lower limit within the permissible RCV% range. In the physical examination group, the relative RI differences among the four methods (excluding the lower limit of RI obtained using the Q-Q plot) were all within the acceptable RCV% range; the relative deviation of the RI of UA with the four methods was within the acceptable RCV% range (excluding the lower RI limit obtained using the Q-Q plot and nonparametric test). CONCLUSION: The Hoffmann and Bhattacharya methods may provide reliable RIs for indirect estimations of urea, creatinine, and UA based on laboratory datasets.

Composite Scaffolds of Gelatin and Fe3 O4 Nanoparticles for Magnetic Hyperthermia-Based Breast Cancer Treatment and Adipose Tissue Regeneration.

Postsurgical treatment of breast cancer remains a challenge with regard to killing residual cancer cells and regenerating breast defects. To prepare composite scaffolds for postoperative use, gelatin is chemically modified with folic acid (FA) and used for hybridization with citrate-modified Fe3 O4 nanoparticles (Fe3 O4 -citrate NPs) to fabricate Fe3 O4 /gelatin composite scaffolds which pore structures are controlled by free ice microparticles. The composite scaffolds have large spherical pores that are interconnected to facilitate cell entry and exit. The FA-functionalized composite scaffolds have the ability to capture breast cancer cells. The Fe3 O4 /gelatin composite scaffolds possess a high capacity for magnetic-thermal conversion to ablate breast cancer cells during alternating magnetic field (AMF) irradiation. In addition, the composite scaffolds facilitate the growth and adipogenesis of mesenchymal stem cells. The composite scaffolds have multiple functions for eradication of residual cancer cells under AMF irradiation and for regeneration of resected adipose tissue when AMF is off.

Combined anterior and posterior approach in treatment of ankylosing spondylitis-associated cervical fractures: a systematic review and meta-analysis.

OBJECTIVE: Cervical fractures with ankylosing spondylitis (CAS) are a specific type of spinal fracture with poor stability, low healing rate, and high disability rate. Its treatment is mainly surgical, predominantly through the anterior approach, posterior approach, and the anterior-posterior approach. Although many clinical studies have been conducted on various surgical approaches, controversy still exists concerning the choice of these surgical approaches by surgeons. The authors present here a systematic evaluation and meta-analysis exploring the utility of the anterior-posterior approach versus the anterior approach and the posterior approach. METHODS: After a comprehensive literature search of PubMed, Cochrane, Web of Science, and Embase databases, 12 clinical studies were included in the final qualitative analysis and 8 in the final quantitative analysis. Of these studies, 11 conducted a comparison between the anterior-posterior approach and the anterior approach and posterior approaches, while one examined only the anterior-posterior approach. Where appropriate, statistical advantage ratios and 95% confidence intervals were calculated. RESULTS: The present meta-analysis of postoperative neurological improvement showed no statistical difference in the overall neurological improvement rate between the anterior-posterior approach and anterior approach (OR 1.70, 95% CI 0.61 to 4.75; p = 0.31). However, the mean change in postoperative neurological function was lower in patients who received the anterior approach than in those who received the anterior-posterior approach (MD 0.17, 95% CI -0.02 to 0.36; p = 0.08). There was an identical trend between the anterior-posterior approach and posterior approach, with no statistically significant difference in the overall rate of neurological improvement (OR 1.37, 95% CI 0.70 to 2.56; p = 0.38). Nevertheless, the mean change in neurological function was smaller in patients receiving the anterior-posterior approach compared with the posterior approach, but there was no statistically significant difference between the two (MD 0.17, 95% CI -0.02 to 0.36; p = 0.08). CONCLUSIONS: The results of this review and meta-analysis suggest that the benefits of the anterior-posterior approach are different from those of the anterior and posterior approaches in the treatment of ankylosing spondylitis-related cervical fractures. In a word, there is no significant difference between the cervical surgical approach and the neurological functional improvement. Therefore, surgeons should pay more attention to the type of cervical fracture, the displacement degree of cervical fracture, the spinal cord injury, the balance of cervical spine and other aspects to comprehensively consider the selection of appropriate surgical methods.

Detection of rare CTCs by electrochemical biosensor built on quaternary PdPtCuRu nanospheres with mesoporous architectures.

Circulating tumor cells (CTCs) are promising liquid biopsy biomarkers for early cancer detection and anti-cancer therapy evaluation. The ultra-low abundance of CTCs in blood samples requires highly sensitive and accurate detection ways. In this study, we propose the design of a dual-recognition electrochemical biosensor to improve both the specificity and signal response. PdPtCuRu mesoporous nanospheres (PdPtCuRu MNSs) with excellent three dimensions (3D) nanopore structures were synthesized by one-pot method and connected to mucin 1 (MUC1) aptamer to serve as signal amplification probe. Besides, superconductive carbon black, Ketjen Black (KB), and gold nanoparticles (AuNPs) modified organometallic frame (CeMOF-Au) were combined to work as signal transducer. The characteristic branching structure of KB provides abundant contact points to load CeMOF-Au to heighten the interface electron transfer rate. In addition, AuNPs were reduced on the surface of CeMOF, which could effectively bind the capture antibody and further enhance the conductivity. Under the optimized condition, the limit of detection (LOD) of the as-constructed biosensor was less than 10 cells mL-1 for model A549 cells, and showed good specificity and accuracy in spiked serum samples. We envision the as-proposed electrochemical biosensor would alternate as a useful tool for the clinical detection of CTCs for cancer diagnosis.